Hello. It is talonsoft webinar. We're going to talk about HR trends. My name is nellyville Linden, digital content manager at talent soft and I am here today with Alex on probation, ski Co, founder of talent, soft and also author of the book unique welcome Alex. Hello Ann. I'm also here with. Marketing and global presales director at Allen Self Welcome Melody. So let's get started, uh, one thing before we dive into the trends is if you have any questions doing this webinar, please feel free to put them in the chat. Alright, let's go first trends that we're going to be talking about is empower yourself to face uncertainty. Alex, I think you can elaborate on this, right? What we are looking at right now is that actually we got a lot of features explaining us that basically everything is going to change on the labor market. We've been told that 85% of the 2030 jobs do not exist today, that of of the American jobs could disappear by 20 years that have our skills could be obsolete by two years. So well, you got features everywhere and even if we do not know exactly what the future will be about. What we are certain about. Is that we cannot know what will be our jobs by 10 years and the problem we are facing. Everyone of us not on his blue colors. Although it's everyone is that if we do not know what the future of work will be all about. How can we deal ourselves? What does a carrier path mean? What kind of skills do I have to develop? We do not know. We just know that some jobs are going to be replaced for sure if you just look at whatever happened in the last decade. With the cashier's yes, when we are going for shopping, we observe that yes, some people have been replaced by machines. If we look at Amazon or Alibaba warehouses. We also know that a lot of jobs have been replaced by machines like in the real humans TV show. You know where you got a warehouse with only robots except one guy supervising these robots. So even if it's not really the case today because robots are not so sophisticated. We know that it could happen, but it's not. Only about warehouses are cashier's. It's also about surgeons because we know that now, thanks to artificial intelligence and virtual reality, they can work from home with a robot doing surgery on a patient. You also know that journalism is threaten the sins now in the times, for instance, you got articles written by AI. AI can also write poetry. Can compose some music so. What is kind of scary is that we felt it would be only about repetitive tasks and activities, and it's wrong. All the activities are concerned, so it means that even the Mac in their consultants, even the lawyers, could be threatened, and that's what the project IBM debater as shown recently debating in front of a real lawyer. So what I want to say here is that if we don't know what the future will be about, but if we know for sure that all our jobs are going to be transformed, either being replaced or. Bascially automated weather it is 50% or 80%, whatever it is. The only thing we can really rely on to determine what kind of job we will be able to occupy, what part of our current job we will keep. Are we collaborate with the machine to do what? The only thing we can rely on is ourselves? It means that if we cannot know the future, we can try to know ourselves better and try to understand what really all our talents are skilled. What makes a singular and so how could we contribute globally to the world, but in particular to company to a team to our job, leveraging something that we got and that someone else. Doesn't have that machine. Couldn't execute and better than that. If we want to adapt in the future, which is highly uncertain, we really need to focus on what we really want to develop. What really matters to us and the problem is that we have all we in a way of being raised. This color system during your studies in our current jobs to earn a living. And we didn't wander enough, but I would really enjoy doing coming at the office on Monday morning. And if we do not find that it will be extremely difficult to invest time and energy to develop skills that once again we do not know about yet. And so the only thing we can rely on is our will to develop ourselves in a specific domain that really matters worse and this questioning about. Sales is really one of the steak of this communicate. And that's why we need technology when he technology to help us in that manner. Yes, exactly. I think if we talk about this, um elodie, how can companies help their people? Or how can, for example, the talents of platform enable people to become more autonomous in this in this phase of questioning themselves? Well, I think that in the very fast changing environment that. Describe before, of course, it is very important to know yourself as a worker, but it's also important to stay active. Don't be too much passive in front of the situation within that their key as an employee is to have the ability to drive to lead your own professional development. So to have a high level of autonomy in your development plan for that at an unsolved, we have two different ways. First, you can design your personalized training path to live love. Both called given business skills, technical skills in your day today as well as kids that match your personal aspiration. For this purpose, you had plans of learning catalog, which offers the bit to see user experience than provides targeted training, where each employee can register depending on their own development plan and then run on their schedule. Another way, and to develop an encourager to me, is to take Part 2 initiatives than for strategy for the organization. This machine is all generally short or mid term projects that can be created by a turn by managers and my employees themselves to solve an issue which is generally the complex issue. And this is a project that required talents and skills from different origins from different teams. This initiatives are available in a talent marketplace where each sample you can apply to the project and this way impact the young and the Scott of their job in the day today. So both are learning catalog and product market place are impactful features to empower every people at work. Yeah definitely. And this brings us to the second trends. We're going to be talking about today, which we've named make your own way. Alex, please enlighten us. As a Indian, I just said before, uh, it's A kind of new approach of work, which is also kind of scary because it's all about questioning ourselves depending on ourselves to develop the skills that will be required tomorrow without exactly knowing that it will be about. And when I say we need technology, it so so becausr technology can help us to know ourselves more than sometimes we do, and that the idea to rely also on data. So it's a complex problem. What we be leaving looking at, for instance Netflix, because Netflix is always. As an example of how it should be, the training catalog should be like Netflix. We would be pushed. Things that are really relevant for us, as if Netflix new ourselves more than us. Actually, I do not like Netflix because the problem of Netflix is that if you have looked Whittier Animal Tarantino movie, you're going to be pushed some Woody Allen and Tarantino movies or Tarantino actress actors till the end of your life. And it's not what I expect from AI. If we're talking about discovering ourselves, it's about in a way highlighting and lightning areas of ourselves that we do not know that we haven't explored. Yet so it would mean that with all our digital footprints. Old data that social media hi, as an all the digital systems we are using currently they got huge amount of data that could be leveraged to tell us. Oh did you know that actually you sleep far less well that you felt you do not eat well neither and so on and so on and back to the labor market. Did you know? That you seem extremely interested into that topic because looking at your clicks, you spend one hour and a half a day reading article about that, but it has nothing to do with your job. Actually, it's just that you seem interested, so you could be pushed a project, someone related to that topic. Problem is to do that. People have to trust the organizations that are going to use and leverage that data and the problem we are facing currently is that the companies that are doing that are mostly the Jaffa to be ATX and we know that what they want from us. It's to turn us into super consumers and we are not interested into that. But we aren't interested in here here in the labor market. It's to discover ourselves to be able to develop skills that we haven't developed yet, but we could be interested in. And so it means that the people and the organization and data scientists and all the people that are working on the algorithms in on the data. They should have very clear and precise intention. Bing we are going to help you to know you and we are going to push you insides that you could be interested in. And if we cannot talk about career path because as we said before, difficult to elaborate attached to something which is totally unknown. We could at least rely on. Once again all these skills we could develop and technology could have real person that matter and that's why I also we have developed. Specific things at down solved. Yes, exactly. Let's take a look at that. Siri, can you tell us how talent source learning offering is presented to start with? The question is, is it interesting based on what Alex told before about Netflix, let me just share a Word With you about the learning. Offer advanced we've seen just before the training catalog and we have something more which is tons of content. Content as a service platform that aggregates more than 300 channels from more than more than 40 vendors so that learning and development managers can design failures content for their employees and their managers. and I talk about this product because the paradox. If you look at it on the screen here is that it actually looks like Netflix Seven. It's yes. OK, so it's a paradox, but we do that on purpose. Is actually to ensure user others, because even if you don't like Netflix like Alex, you probably use it in your day today and you expect to find the same usage in the tools you use at work. So overpriced. We use this navigation inspired by Netflix like solutions. However, the technology behind it is far different because we want to ensure that we don't push similar context to our employees so that they developed. We want to make sure the content we push will help them to take their next step to learn something new. This platform is actually the right level to give love, technical and business skills, but also soft skills that are required to face the future of work. Need to be more and more required. Even one more question since we're looking at this screen, perhaps an obvious one as well. But what role does day to play in all of this? Yes. Nothing like that, you know. And we talked also about how to block people at work for skills and jobs that we really don't know. And that's what we really invest a lot in matching technology. Who is matching? Actually there is no magic. OK, if we don't have the right, reliable and accurate data. We can't push personalized learning activities or any other app opportunities in the day today. So what we do with a concept hub, which is the occurrence of the current offer, is that we offer a central place where we aggregate where we can explore laptop and all these data can be integrated with your entire areas and payroll systems. So this is a solution that ensures that you can get the right picture of your workforce at anytime and this is actually the basis to work on workforce development. And the future of your organization? Yes, thank you. Yes, it definitely all starts with the data and I think that brings us to the next trend Alex, which I think is a talent mining. what I believe is, as we said, is that if you do not have data, you won't have artificial intelligence. So the whole steak is about collecting data. Question is how can we build trust? Trust, meaning people that are confident that if provide data to company for algorithms, it will be used for their own sake. And that's really the question of the decade. What we can see in the pastures is that each time we have been the trust among collective project. This was for instance 20 years ago the Seti project was about contributing in. Providing some enerji with your CPU of your computer. For an Organism that he that was looking for you photos and I was one of them. And so I was contributing to look for you first because I knew what was their quest and how they were using my computers because I had a kind of dashboard showing me my CPU is used ten years after you get the Bitcoins and the bitcoins. Obviously kind of relates to the dark web, so let's not elaborate on that, but it's more about the blockchain. The principle that the very principle of the blockchain is that everyone is contributing to database. In that various transparency that is insured by smart contracts. And the problem we got today, for instance with the small assistants like Google Home like Alex or Siri, is that. We do not know Arvella Bridge data they collect from us each time we asked asked a question, but it's time we talk because it has been shown during last summer that actually Alexa was collecting data all the time. Not only when we were asking questions, but during all our discussions and at worst than that we have discovered that real human beings were listening to our conversation. So it means that. In that it's very example, you totally have a lack of trust and confidence because you do not know whether I'm going to do with your data and you didn't even know that they were doing that. So what we believe in that looking at the past. We got to rely on everyone to get info to create Intel about people that work and we got to provide transparence transparency. We got to provide kind of dashboards monitoring the kind of usage it is done with all the time, and that's what, for instance. Recently we have tried to do with down soft. We have collected data from the Office 365 leveraging. The Microsoft graph. And so it was interesting to discover that someone was spending a lot of time with someone else on a specific topic of sending a lot of emails to very group of experts about another topic. And so it was a very good mean to detect skills that could complete the current HR processes that we support. When you did the individual consents obviously to do so, and user data of people and what we've discovered is that even when the intent is detecting their own skills to push learning material to push projects that maybe we wouldn't have pushed them, people are reluctant about that, so we once again need to build trust, and we need to rely on everyone to contribute to discover talents in a very clear and transparent way. And that's why we are talking about. Donald Maine. Yeah, come back to that for a second. I think in in building that transparency and trust, I think that's where a lot where an important role for HR lies. Yeah, in a way to respond to the people that are responsible for this stressed. Just to keep us in mind, and if they do not take this responsibility honestly, I do not really know who is going to take it. We know that regulations are going to protect us, but protecting us also mean preventing us from getting the benefits from AI. So where is the right balance once again? And this is what we want to elaborate and design and thing. I turned soft and that's also why we have developed specific product about that. And I think another question that comes to mind here is done about it. Obviously a data ownership right if employees are willing to share their data, then that's a question that comes to mind. We believe it's gotta belong to them today. It would belong to the companies that pay for the software that is collecting the data, but it's wrong. I believe that the software belongs to the company that paid for it. But if someone provides the data at the end of the day, it should be in a kind of digital safe. That you can collect a look at. You could erase part of the data, and, uh, obviously. First it should know, uh, I said? What about his work? And so on. And we come back to mind set, it means that we've got to develop another culture around the mindset, and that was also our products help changing. It's changing math, mindsets, changing practices, and that's why this. Is so fascinating that. It's not once again us about pushing another feature. It's about supporting this feature with the change and we got things to more than 12202 hundred 2000 customer. We know that now what can work cannot work with ready to do wet or not and we want to leverage this return of the experience. Yeah, thank you. So coming back to this this change and people taking risks and when it comes to their jobs how can the talents of platform reassure people and support them when it comes to taking risks? The risks that Alex mentioned before, yeah. Sorry I won't go through the GDP are compliance. Please no. In our industry and of course, this compliance is already available in our solution, but we believe that a simple way to create trust and transparency as we discussed before, is to put that up at the hand of people at work. So with that other profile we have designed this profile. Of course, automatically calling that out with the information we have in our solution, but information that has been proved. So this is the first condition to create trust. Second is that this technology allows to suggest skills to be added to the profile, but the employee can accept or reject the suggestion to enrich his profile. And finally, the Anthony himself is free to self declare. New skis, or you aspiration? They want to highlight in their profile. Another way, uhm, we think we can leverage to build trust and transparency around data is to capture data in the flow of work. what I mean is that with our solution, we want to engage with employees and managers in the continuous conversation to ensure that the data for example related to objectives and key results are reviewed regularly and reflect the reality. On the field. And by the way, we believe that you know the traditional annual review process as to be completed with this constant conversation with this continuous review of objectives with continuous conversation that you can feel the string. Here we support this regular conversation between employees and managers, one to one meetings, and we create a culture of feedback that we choose to collect data that are perfectly aligned with what happened in the day-to-day of our employees and managers. So we really think that this is the right tool for managers to align goals. Corporate goals with teams, objectives with individual objectives and keep the data up to date in the day today and being more reliable, I think yes, and I think this continuous conversation also sounds like a really good way to continuously work on building that trust and being transparent. So yes, I think that's good, very good thing, and I think this brings us. To the last trends. The 4th trends we're going to be talking about is one of my favourites and its dream teams. Alex please. We're talking about dump mining and the strength to rely on everyone to get some Intel and collect some data. And actually, it's kind of the same to solve problems today. As an entrepreneur, I can tell you I could believe that after 20 years of entropy nor ship, I could solve the problems. Alone, because obviously I can believe that situations are going to repeat and I only already had a solution and it's totally wrong. what I discovered, and I'm amazed about every day is that actually knew problems appear at a pace that is increasing. Each problem is more and more complex, requires more and more skills from different areas are areas of expertise. And so actually, every day I realize that I need a bunch of people around me to solve the problems I'm facing and What is interesting is that not only I need people, but I need people that do not think in the same way that do not come from the same environment that have not the same diplomas. I've not the same experiences. Why? Because some problems I'm facing today are problems that no one's ever faced before. And it's a case for every companies, every industries, every geographies. It means that you do not have to focus only on the past. But you got to rely on what could people do and what could people do together. And so it's a good news. It means that we got to think in terms of teams, not in terms of individuals, not even individual heroes. And it's about. Aligning The goals of everyone to ensure that they are fighting in a way for the same purpose. I think you've got an example here about oceans 11, right? Yeah, so that was an example that I love because when you look at all these Hollywood movies and looking at oceans 11 orations H recently with the only women what we appreciate in that movie is this moment where I talking about patience. 11 for instance you got George Clooney gathering steam. And the front part of the movies that you discover the story of everyone you understand are different. There are, but you understand that everyone of us is going to bring something to the team. A specific skill as specific, a talent that is going to be necessary to solve the very problem they want to solve and the talent of here George Clooney. Meaning the manager. Having all this, Terrance is not too knowing everything. It's about gathering the right people and giving them the will. The energy to work together and create a soul, and I believe that for the next decade the state of HIS will be not around creating individual heroes. It will be about helping managers to create. Great teams, and that's a specific topic we address right now with our product, yes. I think we agree eluded at the key ingredient for every great team is collaboration. How can companies reinforce their collaboration with details of tools? Well, we believe that to encourage teamwork, we need to avoid forcing users to log into multiple tools at the time where they need to collaborate. We need to bring our processes. Our HR process is where the user is in the day today. This is what we do is our integration with Microsoft Teams for example. So Microsoft Teams need collaborative solution and then it allows to employees and manager to collaborate around proteins and Talonsoft is integrated to this tool to allows for example employees and managers to update regularly. Their objectives and to perform key actions like you know, approving Ben appraisal form for example, like accepting their learning action which is pushed by the temples within teams. Like any any action in in the floor, they were basically and this is a very good way to improve and encourage collaboration in the workplace. The Azure still have your first transaction, Anna deeper engagement. Also affordable users. And I'm joining forces collaboration. Alex Talk a little bit about this before we do need to ask some bull patterns. That can work perfectly together to achieve the best results that would that would make our company organization more efficient, more productive. And they need to complement each other for that purpose you need to attract to hire people from different origins from different backgrounds, different mindsets, even untypical profiles as you mentioned before Alex and with our solution tenants of the CRM, talents of candidate relationship management. You can assemble things from everywhere you can. Assemble transform schooling man's job fairs, social networks, and by targeting your Contacts with specific communication, you can create a long-term relationship and maximize the chance to turn new Contacts into candidates at some point. The good thing in the collaborative part of the solution is that to ensure that your future employee match with the soul with the soul of the rest of your team, you can share your talent pools to encourage your team members to collaboratively screen and give feedback on the candidates. This is what will make sure in the future that collaboration is easier. Yes, on the team's work Better Together, even Better Together. Thank you very much. I don't know Alex. Do you have any last words to say about this new exciting error of HR trends? While I appreciate about these transcend decade, we are jumping in that we really understand that it will be about finding the right balance between the current situation, all the processes we have built, all the states of the last decade that we haven't solved all of them yet. But we got also to prepare for the problems in the states of this decade and finding the right balance equilibrium between what the human beings are ready to do to accept contribute to today and encouraging them and finding the ways finding the means for them to be more secure in what could happen here. It is in the jobs that are about to come, or in the algorithms that were about to. Uh, use, I believe we can contribute in finding this balance between technology change, human beings, mindsets, and so it's. A more complete a dedicated. It won't be about being flashy about, well effect. It will be about really company people and I really appreciate that. Sounds to me like a beautiful ending to this webinar. I want to thank everyone for listening. I want to thank you, a lady. I want to thank you, Alex and that's it for us by. Yeah.
2020 is here and it brings new challenges and opportunities! It’s time to share our predictions on what will be leading HR Trends this year…. And perhaps the decade!
Alexandre Pachulski, Elodie Champagnat, and Neelie Verlinden will decrypt what will shape HR in 2020. Data, Artificial Intelligence, Teams, Training... how can we help build the future of HR?